What is a Data Structure?

There is no doubt that data is treated as the most powerful tool for businesses to survive and rise above the competition in today’s challenging and competitive world. In this regard, the data structure is considered the programmatic way of storing and organizing the data so that the programmers can use it efficiently to perform further operations. Unfortunately, nowadays, most companies need help to collect and store data in an organized way. So they often face problems using, processing, or retrieving the stored data for further operations. That is why it has immense significance among business owners to organize and store data systematically.

Types of Data Structure

Usually, the data structure can be categorized into two main types: linear and non-linear. Let’s explore each type in detail.

Linear Data Structure

It is most commonly used to store the data one after the other sequence. As all the elements are stored in a particular order, programmers can easily implement those elements to perform further operations. However, the linear category is not ideal in the case of any complex program.

Types of Linear Data Structure

The linear category is further divided into the following types:

Array

An array is treated as a collection of similar data elements stored at contiguous memory locations. However, the type of data you wish to store in array form largely depends on the programming language you are using.

Stack

A stack is a collection of stored elements based on the Last In, First Out (LIFO) method. That means the element stored at last will be out first. You can compare it with a pile of plates where the plate stored at last will be removed first.

Queue

A queue is a collection of stored elements based on the First In, First Out (FIFO) method. That means the element stored at first will be out first. You can compare it with a queue of people standing in front of a ticket counter where the first person in the queue will receive the first ticket.

Linked List

A linked List is a collection of data elements connected based on a series of nodes. However, every node includes the data items along with the address to the next node.

Non-linear Data Structure

In this category, elements are stored without any sequence; every element can contain multiple paths to connect with one or multiple elements. Besides that, it supports multi-level storage. However, this category may be complex to implement, but it is proven extremely efficient while utilizing memory for high-volume multi-structured data.

Types of Non-linear Data Structure

This category is further divided into the following types:

Tree

Tree data structures are treated as a set of nodes in which the topmost node is known as the root node, and the bottommost nods are known as leaf nodes. Each node can have multiple child nodes but only one parent node.

Types of Trees

It is possible to find the following types of trees in the data structure:

• AVL Tree
• Binary Search Tree
• Binary Tree
• General Tree
• N-ary Tree
• Red Black Tree

Graph

A graph is treated as a pictorial representation of a set of nodes in which every node is connected to others through links that are known as edges. Every interconnected node is known as a vertex and is commonly represented by a point.

Types of Graphs

It is possible to find the following types of popular graph-based data structures:

• Bipartite Graph
• Complete Graph
• Connected or Disconnected Graph
• Cyclic Graph
• Digraph Graph
• Directed Acyclic Graph
• Finite Graph
• Infinite Graph
• Labeled Graph
• Multi Graph
• Null Graph
• Pseudo Graph
• Regular Graph
• Simple Graph
• Subgraph
• Trivial Graph
• Vertex Labelled Graph

Apart from the above types, it is further possible to divide the data structure into two categories:

Static Data Structure

This type of structure always has a fixed size allocated during the compile time. So, it is impossible to change the maximum size as it is already fixed.

Dynamic Data Structure

Unlike the static structure, this type always has the flexibility to change its maximum size. So, programmers can change the maximum size as per their needs.

Final Thoughts

We hope now you have gained in-depth knowledge about data structure and its types. There is no doubt every type comes with its own advantages as well as disadvantages. However, this knowledge will definitely help you to select the right one for your next project.